This application is a competitive renewal to complete phase II of a genetic study aimed at mapping genes for human obesity. In phase I of this study, the focus was on developing a sample suitable for mapping genes with large effects, primarily major genes segregating in as few as 25 to 30% of families with extreme obesity. To accomplish this goal, a sample of 100 multiplex nuclear families with at least one severely obese sibling pair, one lean parent and one lean sibling was developed. These families include 184 independent affected sibling pair equivalents. In genotyping and linkage analyses, the initial focus was on chromosome regions associated with obesity syndromes in humans and regions homologous to animal obesity mutants. A 10-20 cM genome wide screen of the first half of the sample has also been completed with over 85,000 genotypes of 400 markers. Linkage was detected between extreme obesity and microsatellite markers flanking the human obese (OB) gene locus on chromosome 7q31. In phase II, the plan is to enlarge the family sample and conduct appropriate searches to map genes that make moderate but significant contributions to obesity. The loci should include major genes which segregate in as few as 6 to 26% of families with extreme obesity and quantitative trait loci accounting for as little as 25% of the total trait variance. Specifically, the following is proposed: 1) the sample will be increased to 275 nuclear families (175 additional) with 504 independent obese sibling pair equivalents, 59 lean pairs and 107 discordant pairs (a total of 1,061 siblings with 1,870 non-independent pairings), 2) complete genotyping in candidate regions as well as a 10 cM genome wide scan using microsatellite markers 3) conduct linkage analyses using primarily nonparametric linkage methods, and 4) conduct association studies of parent-affected child pairs to help in localizing genes within regions identified through linkage. The investigators state that the identification of human obesity genes will improve accuracy of genetic risk estimates, enhance efficacy of prevention programs, and permit the development of effective and specific therapies.